Video systems often estimate pixel values for pixels that are not available in the original video data, such as when converting interlaced video to deinterlaced video or when upscaling video to a higher resolution. Conventional techniques for estimating a pixel value for a missing pixel typically rely on some form of interpolation between lines above and below the line on which the missing pixel will be located. Often, such interpolation processes utilize edge detection to identify whether a pixel value being estimated lies along an edge in the content of the frame, and interpolate for the pixel value accordingly. However, many of these edge-dependent interpolation processes fail to account for the direction of the edge, which can lead to significant interpolation errors and thus introduce undesirable visual artifacts, and those conventional interpolation techniques that do account for the direction of the edge often require considerable processing effort to do so, such as requiring analysis over many successive fields. Moreover, conventional edge-dependent interpolation techniques fail to properly evaluate the validity of the detected edge, thereby frequently calculating incorrect pixel values based on a falsely-detected edge.